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Abstract Introduction Blast transformation (BT) in CMML occurs in 15-30% of patients (pts) with a median overall survival (OS) <6 months (mo). While clonal evolution can be observed, biological mechanisms of BT remain unknown for many pts. Using paired samples from chronic phase (CP) and at BT, this study defines the cytogenetic and molecular landscape of BT-CMML. Methods BT-CMML pts from Mayo Clinic (n=153, 31%), MD Anderson (n=195, 40%), and 7 centers of the Groupe Francophone des Myélodysplasies (n=145, 29%) were included after IRB approval. ICC 2022 criteria defined CMML and AML. Pt data were collected at initial diagnosis or referral at CP and again at BT. Clonal dominance was inferred from a natural log-fold difference of mutation variant allele fractions (VAF). OS was censored at allogeneic stem cell transplant (alloSCT). Single-cell multiomic analyses used the Tapestri platform (Mission Bio). Statistics used R. Results Among 1,883 cases of CMML with a median follow up of 96 mo, 493 (26%) underwent BT. The median age at CP and BT was 69 and 71 years, respectively. BT-CMML pts were predominantly male (69%) and had proliferative CMML (53%) or CMML-1 (69%) in CP; 39% and 33% were considered high-risk by CPSS-Mol and BLAST-Mol criteria, respectively. The median time to BT was 16 mo (interquartile range 7-35 mo) and was not different in males vs females (p=0.60). Compared to their CP parameters (p<0.001 each), pts at BT had lower median hemoglobin (10.8 vs 9.2 g/dL) and platelets (100 vs 44 x109/L) but higher leukocytes (13.9 vs 16.3 x109/L), peripheral blasts (0% vs 14%), and bone marrow blasts (6% vs 32%). Blasts exhibited mostly monocytic (57%) or immature myeloid (40%) differentiation. Abnormal karyotypes (AK) were more prevalent at BT (25% vs 62%, p<0.001). Among 318 pts with paired karyotype data, 221 (69%) had a normal karyotype (NK) in CP, of which 123 (56%) remained normal at BT and 98 (44%) acquired new abnormalities. Conversely, 97 (31%) pts had an AK in CP, of which 67 (69%) acquired abnormalities or increased clonal metaphases (6%), 23 (24%) remained stable, and 7 (7%) reverted to a NK at BT. Overall, 46% acquired and 8% lost a clonal cytogenetic abnormality, while 46% remained unchanged. Numeric (37%) and structural (30%) changes were most common. Complex (12% vs 3%) and monosomal (5% vs 2%) karyotypes were more frequent at BT than in CP. Only 6 (2%) pts acquired an AML-defining rearrangement at BT. Mutational data were available for 248 paired cases. The number of somatic mutations was higher at BT (median 3 vs 4, p<0.001). Mutations in RUNX1 (27% vs 39%), NRAS (23% vs 33%), KRAS (11% vs 17%), FLT3 (6% vs 15%), NPM1 (0% vs 11%), IDH2 (5% vs 11%), and CEBPA (3% vs 10%) were more frequent at BT (all p<0.05). At BT, the average VAF of the dominant clone increased in 32%, decreased in 35%, and remained unchanged (delta ≤5%) in 33%. The most frequent dominant clones both in CP and at BT had mutations in TET2 (8% vs 4%) or co-dominant mutations involving SRSF2-TET2 (7% vs 3%). Mutational clonal evolution was observed in 72%, with mutations gained in 45% and lost from the dominant clone in 19%. The most gained mutations at BT were in NRAS (15%) and RUNX1 (13%). Single cell proteogenomic analyses in 4 selected CP and BT pts shed light on the impact of NRAS and RUNX1 mutations on clonal hierarchies and differentiation. Among 196 fully evaluable cases, a new cytogenetic and/or molecular aberration was uniquely gained in 106 (54%) cases and lost in 9 (5%), with 40 (20%) both gaining and losing a genetic alteration. Forty-one (21%) patients had no identifiable genetic change between CP and BT, suggesting driver alterations outside of that detected by routine analyses. Median OS was 31 mo from CMML diagnosis and 5.6 mo from BT. Compared to supportive care, treatment in CP did not prolong median time to BT (14 vs 17 mo, p=0.91) or OS (35 vs 29 mo, p=0.05), regardless of intensity. After BT, median OS was 1.2 mo with supportive care (n=83), 8.7 mo with a hypomethylating agent (HMA, n=39), 10 mo with HMA plus venetoclax (n=37), 7.8 mo with chemotherapy (n=91), and 31 mo in pts who underwent alloSCT (n=57). Conclusions In this large BT-CMML cohort, cytogenetic (46% gained, 8% lost) or mutational (45% gained, 19% lost) driver events were identified in 79% of pts, with 21% having no identifiable changes by conventional testing. Whole genome/transcriptome analyses are underway in this subgroup to identify novel drivers of BT.

Abstract Background: While mutations in the fms-like tyrosine kinase 3 (FLT3) gene are well-established adverse drivers in acute myeloid leukemia (AML), their role in myelodysplastic syndromes (MDS) and chronic myelomonocytic leukemia (CMML) remains insufficiently defined. Methods: We conducted a retrospective multicenter study of 115 patients with FLT3-mutated (FLT3mut) MDS (n=63) or CMML (n=52), comparing their clinical, genomic, and therapeutic characteristics at diagnosis or first referral to 677 FLT3 wild-type (FLT3wt) controls (MDS n=388; CMML n=289) using multivariate analyses and propensity score matching (PSM). Results: FLT3mut MDS and CMML exhibited a proliferative phenotype with higher leukocyte and neutrophil counts and lower platelet levels (p<0.02); in MDS, median white blood cell counts remained below 13,000/µL. In MDS, FLT3mut cases were enriched in the MDS with increased blasts subtype (57% vs 39%, p=0.01) and favorable-risk cytogenetics (64% vs 41%, p<0.01). Genomically, FLT3mut MDS showed higher frequencies of NRAS, KRAS, PTPN11, RUNX1 and CBL co-mutations (p<0.05), and a markedly lower prevalence of TP53 mutations (2% vs 36%, p<0.001). In CMML, FLT3mut cases were more often transfusion-dependent (50% vs 23%, p<0.01), classified as CMML-2 (39% vs 25%, p=0.04), and enriched in ASXL1 (68% vs 47%; p<0.01) and SETBP1 (24% vs 8%; p<0.01) mutations. Notably, they exhibited multi-hit TET2 mutations less frequently than FLT3wt CMML (27% vs 53%, p=0.01). After adjusting for age, sex, and allogeneic stem cell transplantation, FLT3 mutations were independently associated with worse outcomes. To further assess the prognostic impact of FLT3 mutations, we conducted PSM analyses using a 1:1 ratio of FLT3mut to FLT3wt patients, adjusting for key clinical and biological confounders. In MDS, matching was based on age, sex, bone marrow blast percentage, and cytogenetic risk category; in CMML, variables included age, CMML-2 subtype, peripheral blood counts, normal karyotype, and ASXL1 mutation status. After matching, FLT3mut MDS cases showed significantly shorter overall survival (OS; 19.9 vs 44.2 months, p=0.046) and leukemia-free survival (LFS; 13.8 vs 37.1 months, p=0.023) compared to FLT3wt patients. Similarly, in CMML, FLT3mut patients experienced inferior OS (30.4 vs 67.2 months, p=0.017) and LFS (17.2 vs 65.6 months, p=0.014). Competing risk models confirmed a markedly increased cumulative incidence of AML transformation in both FLT3mut MDS and CMML (p<0.001), without significant differences in the risk of non-leukemic death. Among FLT3mut cases, tyrosine kinase domain mutations (FLT3-TKD) were associated with superior survival compared to internal tandem duplications (FLT3-ITD; MDS hazard ratio [HR]: 0.28, p=0.003; CMML HR: 0.34, p=0.012). FLT3 allelic ratio (AR), assessed by conventional PCR in 63 patients (MDS n=34, CMML n=29), provided additional prognostic value. An AR ≥0.21 identified a subgroup with significantly shorter OS (MDS: 24.4 vs 38.8; CMML: 6.7 vs 30.4 months) and LFS (MDS: 9.0 vs 18.5 months; CMML: 5.8 vs 30.4 months; all p<0.05), supporting the utility of quantitative FLT3 assessment in clinical risk stratification. FLT3 inhibitors (FLT3i) were administered in combination with hypomethylating agents (HMA) to 16 (27%) FLT3mut MDS and 15 (33%) CMML patients. Compared to HMA, FLT3i treatment was associated with higher overall response rates (MDS: 69% vs 22%, p<0.01; CMML: 73% vs 35%, p=0.06). Molecular clearance, defined as post-treatment reduction in AR to ≤0.01, was observed more frequently with FLT3i than with HMA (MDS: 56% vs 10%, p=0.03; CMML: 60% vs 20%, p=0.09). FLT3 clearance was associated with prolonged survival. In MDS, median OS and LFS were 66.0 vs 14.5 (p=0.12) and 29.0 vs 9.9 months (p=0.056), respectively; in CMML, it was 37.6 vs 14.6 months for both OS (p=0.043) and LFS (p=0.032). Conclusions: This study expands the current understanding of FLT3mut MDS and CMML by characterizing their clinical, molecular, and therapeutic features in the largest multicenter cohort reported to date. These cases exhibit a proliferative phenotype, frequent co-mutations in RAS pathway genes, and an elevated risk of leukemic transformation. Quantitative assessment of FLT3 allelic burden refines prognostication beyond mutation status alone. The observed associations between FLT3 inhibitor use, molecular clearance, and improved outcomes support further evaluation of targeted strategies in selected patients.

Abstract Introduction The 2022 WHO/ICC classifications of myeloid neoplasms (MNs) incorporated genomics into the existing clinicopathologic framework, defining new (mono)genetic entities. However, this iterative approach resulted in a mix of pathologically and genomically-defined entities, reliant on arbitrary thresholds and historically-derived boundaries between entities. We hypothesised that integrating genomics with other features, de novo from first principles, might better incorporate modern molecular knowledge to define the biological continuum, evolutionary links and overlapping features across MN. Methods The discovery cohort comprised 6484 thoroughly annotated pts. Contemporary diagnoses included 1817 AML, 1695 MDS, 737 MPN, and 1101 MDS/MPN. Non-malignant pts (AA/CHIP/CCUS/ICUS) were included to explore beyond current neoplastic boundaries. 1407 pts had ≥1 follow-up sample/s. Validation was performed in an independent international cohort (n=2012). An unsupervised random forest algorithm was used to integrate status (and VAF) for 28 mutations, karyotypes, CBC features, sex and age (total parameters 144). Features were selected for potential to be independent of BM sampling. Proximity-based multidimensional scaling/PCA were used to visualize latent structure and identify variance-driving features. Results The model projected pts onto a continuous 3-dimensional space. We first applied clustering seeking 1st-order structure, revealing 4 major clusters (C1–C4). These were further subdivided into 58 distinct subclusters (SCs) by an unsupervised iterative clustering approach. All SCs were enriched for distinctive features, with diverse associations linking genomics to clinicopathological/outcome features. Notably, contemporary diagnoses were distributed widely throughout this landscape, with 9/58 SCs containing cases spanning multiple WHO/ICC MN categories. C1 displayed the most internal heterogeneity, with admixed AML, MDS and MDS/MPN pts. It naturally subdivided down to 4th-order subclustering. Ten SCs were dominated by splicing factor mutations. For example, SF3B1MT segregated into 3 SCs, alone or with high-VAF TET2/ASXL1 or DNMT3A mutations. A separate TET2/SRSF2 SC associated with elevated monocyte%, reflecting a discrete CMML-phenotype genomic entity. NPM1MT formed a distinct SC with FLT3-ITD, distinguished further by VAFs of FLT3, TET2, and NRAS. Current genomically-defined AML subtypes separated in the 4th subclustering. C2 encompassed classical MPN driver mutations across 6 SCs, including a distinct CALRMT group and others defined by variable JAK2 VAFs, co-mutation patterns and other CBC features: eg high-VAF SF3B1MT correlated with PB blast%, and concurrent TET2MT with higher Hb/monocyte counts. C3 was characterized by TP53 alterations, with 5 SCs differing by TP53MT burden, 17p lesions, karyotypic complexity and age. Two SCs, one marked by high TP53 VAF+complex karyotype, the other by ch17 lesions, were associated with the worst OS in the whole cohort. C4 contained most known non-malignant pts, dividing into 4 SCs: 2 largely comprising CCUS and AA, while 2 reflect overlaps/convergence between AA and MDS and MPN, respectively. Repurposing single-cell pseudotime analysis suggested multiple disease origins, with various progression trajectories converging on C3. Projecting them onto the model longitudinal samples moved along these derived paths, consistent with their known progression/remission changes, validating the model's biological relevance and predictive utility. Remarkably, the 58 SCs displayed distinct risks of clonal progression and survival. To maximize potential clinical utility we created a pan-MN prognostic score integrating these features. It performed robustly (c-index 0.84), matching/exceeding existing prognostic tools and validated in an independent dataset. Conclusion Integrating clinicopathologic and genomic data we developed ab initio a continuum model of MNs that transcends historical diagnostic boundaries, captures disease evolution and stratifies clinical outcomes. It may better reflect the core biology and natural histories of specific cases, placing more rational boundaries between discrete entities. Potential advantages extend to treatment selection/trial design (in the era of molecularly-targeted therapies) and personalised prognostication throughout each disease course. Expanded validation is needed to resolve complexity in some areas (notably in C2/C4) and validate/refine this prototype framework.

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p<0.001) but higher frequencies than MDS (p<0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p<0.001) but lower than in MD-CMML (p<0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (>94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (>94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p<0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.

Abstract Background and Aims Patients with catecholaminergic polymorphic ventricular tachycardia (CPVT) are at risk for potentially life-threatening arrhythmic events (AEs) even while treated with β-blockers. The aim was to develop a model for individualized prediction of AEs in patients with RYR2-mediated CPVT on β-blocker monotherapy. Methods The derivation and independent validation cohorts included 743 and 129 patients, respectively. AEs were defined as arrhythmic syncope, appropriate implantable cardioverter–defibrillator shock, sudden cardiac arrest (SCA), and sudden cardiac death. Near-fatal or fatal AEs (nf/fAEs) included all AEs except for arrhythmic syncope. Prediction models using Cox regression were developed and internally and externally validated. Results A total of 102 (13.7%) patients in the derivation cohort and 24 (18.6%) patients in the validation cohort experienced ≥1 AE over a median follow-up of 5.1 [interquartile range (IQR), 7.7] and 2.4 (IQR, 4.4) years, respectively. Predictors of AE were arrhythmic syncope or SCA prior to diagnosis and age at β-blocker initiation. In the derivation and validation cohorts, the optimism-corrected C-indices of the models for AE were 0.67 [95% confidence interval (CI) 0.62–0.72] and 0.59 (95% CI 0.48–0.71), respectively. For nf/fAEs, ventricular arrhythmia severity before β-blocker initiation was a fourth independent predictor, and C-indices of the models in the derivation and validation cohorts were 0.74 (95% CI 0.68–0.80) and 0.60 (95% CI 0.47–0.72), respectively. In the derivation cohort, calibration slopes were 1.00 (95% CI 0.59–1.41) for AE and 1.00 (95% CI 0.69–1.32) for nf/fAE. Conclusions These externally validated risk prediction models using clinical parameters accurately distinguished CPVT patients on β-blocker monotherapy at low and high risk for future AEs while treated with β-blockers. These models provide guidance for implementation of clinical management therapies to prevent AEs in patients with CPVT.

Abstract Introduction: Despite treatment advances, ovarian cancer (OC) remains the deadliest gynecological cancer, with a ∼70% mortality rate. OCs initially respond to platinum chemotherapy but often develop resistance. While PARP inhibitors improve relapse-free survival in responsive cases, they do not extend overall survival. This underscores the need for effective combination therapies beyond BRCA status. The lysosomal protein cathepsin L (CTSL) can traffic to the nucleus, where it can regulate DNA repair and serve as a chromatin modifier. We found that nucleoside analog clofarabine (CLF) induces CTSL nuclear trafficking in OC cells. Here we tested the hypothesis that accumulation nuclear CTSL (nCTSL) is a biomarker of sensitivity to DNA damaging therapy in OCs for improved therapeutic options. Methods: To determine the role of CLF induced nuclear CTSL in DNA damage and its synergy with PARP and CRM1 inhibitors in PARP inhibitor–sensitive and –resistant ovarian cancer (OC) cell lines, ex vivo cultures of ascites-derived patient OC cells (OVA-3D spheroids), primary ovarian tumors, and patient-derived xenograft (PDX) models and validated by colony formation assays. Nuclear CTSL localization was determined in subcellular fractionated lysates by western blots and immunofluorescence cytometry (IFC). Tumor regression was determined in vivo using ex vivo cultures of PDX derived cells. Results: In ovarian cancer (OC) cell lines, CLF monotherapy induced nuclear CTSL (nCTSL) in a subset of models classified as CLF-responsive (CLF-r), sensitizing them to the PARP inhibitors olaparib and rucaparib. In CLF-non-responsive (CLF-nr) models, nCTSL induction and therapeutic synergy were observed only with the CLF+olaparib combination. Synergy was detected in 47% of CLF-r and 24% of CLF-nr patient-derived ascites samples (OVA). Mechanistically, CLF induced nuclear import of CTSL via KPNB1 in CLF-r cells, while this import was triggered by the CLF+olaparib combination in CLF-nr cells. CLF also downregulated the nuclear export protein CRM1 (XPO1) in both groups. Knockdown of CTSL in either CLF-r or CLF-nr cells abrogated sensitivity to the combination. Notably, in 29% of OVA samples classified as CLF-resistant (CLF-Res), CLF failed to suppress CRM1 expression. In these cases, CRM1 inhibition with KPT8602 restored CLF+PARP inhibitor synergy. In vivo, CLF-r and CLF-nr PDX models treated with the combination exhibited increased DNA damage, reduced tumor burden, and extended survival. Conclusion: These findings identify nuclear CTSL (nCTSL) induction as a potential biomarker of response to DNA-damaging therapies. The combination of CLF and olaparib represents a promising strategy to overcome drug resistance in ovarian cancer by promoting CTSL nuclear localization and enhancing DNA damage. Citation Format: Prabhu Thirusangu, Ling Jin, Upasana Ray, Anya Zhao, Julie Staub, Xinyan Wu, Xiaonan Hou, Jamison L. VanBlaricom, Syed Mohamed Musheer Aalam, Sun-Hee Lee, Ann Oberg, Nagarajan Kannan, John Weroha, Jeremy Chien, Scott H. Kaufmann, Jamie N. Bakkum-Gamez, Viji Shridhar. Role of drug induced nuclear CTSL (nCTSL) in DNA damage response in cancer- therapeutic implications [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Ovarian Cancer Research; 2025 Sep 19-21; Denver, CO. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl):Abstract nr A050.

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

ABSTRACT Nonsteroidal anti‐inflammatory drugs (NSAID)‐exacerbated respiratory disease (N‐ERD) is a mainly type 2 inflammatory condition that combines asthma, nasal polyps, and hypersensitivity to NSAIDs. Its pathogenesis involves both upper and lower airways, yet most studies to date have examined these compartments separately. It remains unclear whether the molecular mechanisms in the nose, sinuses, and lungs are distinct or overlapping—an important gap, given that clinical manifestations of N‐ERD involve both sites. In this review, we summarize available omics studies—transcriptomics, proteomics, metabolomics, and epigenomics—performed on upper and lower airways in patients with N‐ERD. While omics approaches have revealed new molecular insights, comparisons across studies are limited by heterogeneity in design, controls, and methodology. We emphasize the need for integrated multi‐omics analyses and standardized frameworks to better characterize the disease across airways. Such efforts are essential for identifying robust biomarkers and therapeutic targets and for moving toward a systems‐level understanding of N‐ERD.

Abstract RAS pathway (RASp) mutations induce proliferative features, and promote transformation in chronic myelomonocytic leukemia (CMML). However, the unique clonal landscape and hierarchy of distinct RASp mutations remain unexplored. To characterize the landscape, architecture, and implications of unique RASp mutations in CMML, we evaluated a cohort of 814 patients with CMML. We identified 461 RASp mutations among 342 patients (42%). N/KRAS and CBL mutations were the most common, frequently involved the P-loop or RING domains, respectively, and frequently appeared as dominant events (63% and 65%, respectively). BRAF, NF1, and PTPN11 mutations spanned throughout the gene structure, and frequently appeared as subclonal events (75%, 64%, and 59%, respectively). CBL mutations frequently occurred in codominance with SRSF2 and multihit TET2, and were enriched for KIT mutations. PTPN11 mutations more frequently co-occurred with SETBP1 and DNMT3A mutations, and were infrequently codominant with TET2 or ASXL1. RASp mutations predicted for shorter overall survival (hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.15-2.07; P = .0075) and leukemia-free survival (LFS; HR, 1.67; 95% CI, 1.26-2.20; P = .0011), influenced outcomes of myelodysplastic and TET2 mutant CMML, and cooperated with IDH2 and RUNX1 mutations to induce shorter LFS. These data set the bases for refined genomic classifications of CMML, and underscore the need to develop RAS-directed therapies for patients with CMML.

PURPOSE Neoadjuvant immunotherapy (IO) has become the standard of care for early-stage triple-negative breast cancer (TNBC), but not yet for other subtypes. We previously developed a clinical-grade mRNA-based immune classifier (ImPrint) predicting response to IO that is now being used in I-SPY2.2 as part of the response predictive subtypes. We report the performance of ImPrint in hormone receptor–positive and human epidermal growth factor receptor 2–negative (HR+HER2–) patients from five IO arms. METHODS A total of 204 HR+HER2– (MammaPrint high-risk) patients from five IO arms (anti–PD-1, anti–PD-L1/poly [ADP-ribose] polymerase inhibitor combination, anti–PD-1/toll-like receptor 9 dual-IO combination, and anti–PD-1 ± lymphocyte activation gene 3 dual-IO combination) and 191 patients from the chemotherapy-only control arm were included in this analysis. Patients were classified as ImPrint+ (likely sensitive) versus ImPrint– (likely resistant), using pretreatment mRNA. Performance of ImPrint for predicting pathologic complete response (pCR) to IO-containing arms was characterized and compared with tumor grade (III), MammaPrint (ultra) High2 risk (MP2), and estrogen receptor (ER)-low (ER ≤ 10%). RESULTS Overall, the pCR rate across the five IO arms was 33%. 26% of HR+HER2– patients were ImPrint+, and pCR rates with IO were 75% in ImPrint+ versus 17% in ImPrint–, with the highest pCR rate >90% in a dual-IO arm. In the control arm, pCR rates were 33% in ImPrint+ and 8% in ImPrint–. Tumor grade (III), MP2, and ER-low showed pCR rates in IO of 45%, 56%, and 63%, respectively, with lower pCR odds ratios (OR < 7.5) compared with ImPrint (OR = 14.5). CONCLUSION Using an accurate selection strategy, HR+HER2– patients could achieve pCR rates similar to what is seen with best neoadjuvant therapies in TNBC and HER2+ (ie, pCR rate >65%-70%). ImPrint, an Food and Drug Administration IDE-enabled assay, may represent a way to identify HR+HER2– patients for IO that best balances likely benefit versus risk of serious immune-related adverse events.